For large-scale computing systems such as mainframes and/or distributed systems that process huge numbers of transactions, performing testing and quality assurance of software application code changes before implementing the code changes in production was a daunting task. A typical new release of such application code can contain hundreds of changes that require intensive and time-consuming testing procedures before being rolled out to production.
Often, a performance test of such code changes would take several weeks and could not adequately be monitored while the test was being executed to determine errors or other problems with processor performance and/or transaction performance that result from the code changes. Instead, it would take weeks for a quality assurance team to assess the performance test data after the fact and then provide its feedback, which would slow down the development, testing, and production rollout of software code to these large-scale systems.